The virtual course "A crash course in causality: inferring causal effects from observational data - Virtual Course - Coursera", is a course with different contents and offers video classes of Approx. 18 hours to complete. Explore its essential features, and click the orange button for detailed information on the Coursera e-Learning platform.
We've all heard the phrase "correlation does not equal causation." So what is equal to causality? This course aims to answer that question and more! Over a 5-week period, you'll learn how causal effects are defined, what assumptions are needed about your data and models, and how to implement and interpret some popular statistical methods. Students will have the opportunity to apply these methods to sample data in R (free statistical software environment). By the end of the course, students should be able to: 1. Define causal effects using potential outcomes 2. Describe the difference between association and causation 3. Express assumptions with causal graphs 4. Implement various types of causal inference methods (e.g. variables instrumental, inverse probability of treatment weight) 5.
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*You save up to USD$500 in 12 months, when you go from paying USD$59 for a monthly subscription, to an annual subscription with the promotion. The normal annual subscription is USD $399. With the promotion you will only pay USD $299. Find out everything by clicking the yellow button.
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